3D guiding assisted augmented assembly technology with rapid object detection in dynamic environment

Chengshun Li, Xiaonan Yang*, Yaoguang Hu, Shangsi Wu, Jingfei Wang, Peng Wang

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

摘要

In the field of industrial assembly, augmented reality (AR) technology has played an important role and demonstrated its enormous development potential in the future. With the current development of product assembly towards customization and diversification, it is difficult to meet the requirements of augmented assembly (AA) by relying on static instructions registered with markers. However, most augmented assembly guidance systems used for dynamic environments are complex, cumbersome, and exhibit high latency, significantly impacting the user experience. In addition, the narrow field of view (Fov) of AR glasses also limits its further application in industrial scene. In response to the above issues, this article proposes an improved 3D guiding assisted augmented assembly technology. Firstly, a lightweight model Yolov7-Slim is proposed to achieve object detection on 2D images, which reduces File size by 26.7 % and improves running speed by 15.3 % compared to the Yolov7-tiny model. Secondly, a 3D positioning algorithm is proposed to achieve the rapid conversion of 2D coordinates to 3D coordinates. Finally, a user-oriented two-stage guidance mechanism is designed to compensate for the limitation of the narrow Fov of AR glasses. To quantify the performance of proposed technology, a 3D guiding assisted augmented assembly system (3DG3AS) was developed and validated in a reducer assembly experiment.

源语言英语
文章编号102857
期刊Advanced Engineering Informatics
62
DOI
出版状态已出版 - 10月 2024

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